Embodiments of the present disclosure relate generally to diagnostic imaging, and more particularly to methods and systems for fast and iterative image reconstruction.
Non-invasive imaging techniques are widely used in diagnostic imaging applications such as security screening, quality control, and medical imaging systems. Particularly, in medical imaging, non-invasive imaging techniques such as computed tomography (CT) are used for unobtrusive, convenient, and fast imaging of underlying tissues and organs. Some CT systems employ direct reconstruction techniques such as filtered back-projection (FBP) that allow reconstruction of a three-dimensional (3D) image data set in a single reconstruction step. Thus, the direct reconstruction techniques are generally fast and computationally efficient.
Alternatively, some CT systems employ iterative reconstruction techniques that iteratively update a reconstructed image volume. Typically, the iterative reconstruction techniques are employed to provide greater flexibility in imaging applications than available when using the direct reconstruction techniques. Specifically, the iterative reconstruction techniques find use in imaging applications that entail selective and/or interactive enhancement of imaging metrics and/or protocols based on specific requirements. For example, the iterative reconstruction techniques provide greater flexibility in configuring acquisition geometry and/or modeling physical effects to improve one or more imaging metrics such as reducing radiation dose, noise, and/or other imaging artifacts.
Iterative reconstruction techniques, however, involve long and complex computations that are generally much slower than the direct reconstruction techniques. Certain techniques have been proposed for reducing computational costs of iterative reconstruction, for example, using ordered subsets (OS) or relaxation factors. OS algorithms, in particular, are used in CT imaging to accelerate image reconstruction by using only a subset of measured projection data in each image update. Although, using only a subset of the measured projection data in the OS algorithms entails approximations, the OS algorithms provide dramatic initial acceleration. Such conventional OS algorithms, however, still employ a number of iterations to converge and involve long computations, thus limiting use of the OS algorithms in clinical settings.